Image processing apparatus, image processing method, and non-transitory computer-readable medium for social distancing display

This application is a Continuation of U.S. application Ser. No. 18/007,799, filed Dec. 2, 2022, which is a National Stage of International Application No. PCT/JP2021/016301 filed on Apr. 22, 2021, which claims priority benefit from Japanese Patent Application 2020-098401 filed on Jun. 5, 2020, the contents of all of which are incorporated herein by reference.

The present invention relates to an image processing apparatus, an image processing method, and a program.

Image processing has been used for various purposes in recent years. For example, Patent Document 1 describes, in a system for keeping a reaching range of droplets from a first target person out of a breathing region of a second target person by adjusting an environment in a space, determining positions and orientations of the faces of the first target person and the second target person by image processing.

Patent Document 1: International Application Publication No. WO 2020/044826

In order to reduce a risk of contracting an infectious disease, it is important to avoid a location where contraction of an infectious disease may occur. However, it is difficult to understand likelihood of contracting an infectious disease at such location. An object of the present invention is to facilitate understanding likelihood of contracting an infectious disease at a target location.

an image processing unit that, by processing an image including a plurality of persons, computes, for a person being at least part of the plurality of persons, a first distance being a distance to the closest person to the person; and a risk information generation unit that, by using the first distance, generates infection risk information being information about a risk of contracting an infectious disease or a safety factor of not contracting an infectious disease in a target region being a region included in the image. The present invention provides an image processing apparatus including:

performing image processing of, by processing an image including a plurality of persons, computing, for a person being at least part of the plurality of persons, a first distance being a distance to the closest person to the person; and performing risk information generation processing of, by using the first distance, generating infection risk information being information about a risk of contracting an infectious disease or a safety factor of not contracting an infectious disease in a target region being a region included in the image. The present invention provides an image processing method including, by a computer:

an image processing function of, by processing an image including a plurality of persons, computing, for a person being at least part of the plurality of persons, a first distance being a distance to the closest person to the person; and a risk information generation function of, by using the first distance, generating infection risk information being information about a risk of contracting an infectious disease or a safety factor of not contracting an infectious disease in a target region being a region included in the image. The present invention provides a program causing a computer to perform:

The present invention facilitates understanding likelihood of contracting an infectious disease at a target location.

Example embodiments of the present invention will be described below by using drawings. Note that, in every drawing, similar components are given similar signs, and description thereof is omitted as appropriate.

1 FIG. 10 10 20 is a diagram for illustrating a usage environment of an image processing apparatusaccording to an example embodiment. The image processing apparatusis used with an image capture apparatus.

20 20 20 20 10 For example, the image capture apparatusis a fixed camera and repeatedly captures images of a region where a plurality of persons such as a large number of unspecified persons come and go (hereinafter described as a target region). Therefore, an image generated by the image capture apparatusincludes a plurality of persons. While an image generated by the image capture apparatusmay have any frame rate, the frame rate may be, for example, a frame rate for constituting a dynamic image. Then, the image capture apparatustransmits the generated image to the image processing apparatus.

20 10 10 By processing an image generated by the image capture apparatus, the image processing apparatuscomputes the space between persons in the target region, that is, the distance between a certain person (hereinafter described as a reference person) and the closest person to the person (hereinafter described as a first distance). Then, by using the first distance, the image processing apparatusgenerates information about a risk of contracting an infectious disease or a safety factor of not contracting an infectious disease in the target region (hereinafter described as infection risk information).

1 FIG. 10 20 10 20 20 20 20 In the example illustrated in, the image processing apparatusis connected to one image capture apparatus. However, the image processing apparatusmay be connected to a plurality of image capture apparatuses. In this case, the plurality of image capture apparatusescapture images of target regions different from each other, respectively. Further, each of the plurality of image capture apparatusesexternally transmits an image in association with information for identifying the image capture apparatus(hereinafter described as image capture apparatus-identification information). Thus, infection risk information can be readily generated for each of a plurality of (for example, as many as 100 or more) target regions.

2 FIG. 10 10 110 120 is a diagram illustrating an example of a functional configuration of the image processing apparatus. The image processing apparatusillustrated in this diagram includes an image processing unitand a risk information generation unit.

110 20 110 The image processing unitacquires and processes an image generated by the image capture apparatus, that is, an image including a plurality of persons. As an example, the image processing unitcomputes the aforementioned first distance, with at least a person being part of a plurality of persons as the aforementioned reference person. A specific example of the method for computing a first distance will be described later.

110 Furthermore, the image processing unitperforms another type of processing on the image as needed and generates various types of information.

10 20 110 20 Note that, when the image processing apparatusis connected to a plurality of image capture apparatuses, the image processing unitacquires an image in association with image capture apparatus-identification information of an image capture apparatusgenerating the image.

120 20 120 The risk information generation unitgenerates infection risk information relating to a target region being a subject of image-capturing by the image capture apparatusby using a first distance. As an example, the risk information generation unitdecides whether or not the first distance has a reference value or less and generates infection risk information by using the decision result. The reference value is set based on a so-called social distance. The social distance is a physical distance that should be kept between adjoining persons in order to prevent infection of an infectious disease. Then, the magnitude of the reference value is set based on a main infection route of a target infectious disease. For example, for an infectious disease mainly caused by droplet infection, a value equal to or greater than 1.5 m and equal to or less than 6 m is used as the reference value. Further, for an infectious disease mainly caused by contact infection, a value equal to or greater than 50 cm and equal to or less than 1.5 m is used as the reference value.

120 120 (Method 1) The risk information generation unitcomputes the number of combinations of persons the first distance between whom has a reference value or less for each image and increases a risk indicated by infection risk information as the number increases. Use of this method enables the risk information generation unitto generate infection risk information for each image. 120 120 (Method 2) The risk information generation unitcomputes the per-unit-time number of appearances of a combination of persons the first distance between whom has the reference value or less and increases a risk indicated by infection risk information as the number of appearances increases. In this method, the risk information generation unituses processing results of a plurality of images generated at different timings. 120 (Method 3) In the method 2, the risk information generation unituses the per-unit-time and per-unit-area number of appearances. Note that, for example, infection risk information indicates a risk of contracting an infectious disease or a safety factor of not contracting an infectious disease in a target region. In this case, examples of a method for generating infection risk information from the aforementioned decision result include the following methods.

110 120 Note that, in each of the aforementioned methods, when processing a plurality of temporally continuous images, the image processing unitcan compute the duration of a state in which the first distance has the reference value or less. The risk information generation unitmay increase a risk indicated by infection risk information as the length of the duration increases.

120 Note that there is a method of generating infection risk information without using the first distance. For example, the risk information generation unitmay compute the per-unit-area density of persons in a target region and increase a risk indicated by infection risk information as the density increases.

120 Further, the risk information generation unitmay use the fact by itself that the first distance has the reference value or less as infection risk information.

110 150 20 110 150 150 10 150 10 Further, the image processing unitcauses a storage unitto store an image generated by the image capture apparatus. The image processing unitmay cause the storage unitto store information generated by processing the image in association with the image. Note that the storage unitis part of the image processing apparatusin the example illustrated in this diagram. However, the storage unitmay be an apparatus external to the image processing apparatus.

110 150 150 20 150 110 20 20 150 The image processing unitmay generate the aforementioned information by processing an image stored in the storage unit. In this case, after being temporarily stored in the storage unit, an image generated by the image capture apparatuscan be read from the storage unitat a desired timing and be processed. Note that the image processing unitcan acquire an image generated by the image capture apparatusfrom the image capture apparatusand process the image in real time regardless of existence of the storage unit.

10 130 130 140 140 140 10 10 2 FIG. The image processing apparatusillustrated infurther includes a display control unit. The display control unitsuperimposes, on an image to be processed, a display for causing recognition of a combination of persons the first distance between whom has the reference value or less, that is, a combination of a reference person and the closest person to the reference person and then causes a display unitto display the display and the image. The display unitincludes a display. While the display unitis part of the image processing apparatusin the example illustrated in this diagram, the unit may be external to the image processing apparatus.

3 FIG. 3 FIG. 3 FIG. 150 150 20 150 20 is a diagram illustrating an example of information stored by the storage unit. In the example illustrated in this diagram, the storage unitstores an image generated by the image capture apparatus(described as image data in) in association with information for determining a date and time when the image is generated (such as a date and time itself or a frame number). Further, the storage unitstores an image generated by the image capture apparatuswith information acquired by processing the image (described as an analysis result in). Note that the analysis result may include infection risk information.

4 FIG. 10 10 1010 1020 1030 1040 1050 1060 is a diagram illustrating a hardware configuration example of the image processing apparatus. The image processing apparatusincludes a bus, a processor, a memory, a storage device, an input-output interface, and a network interface.

1010 1020 1030 1040 1050 1060 1020 The busis a data transmission channel for the processor, the memory, the storage device, the input-output interface, and the network interfaceto transmit and receive data to and from one another. Note that the method for interconnecting the processorand other components is not limited to a bus connection.

1020 The processoris a processor provided by a central processing unit (CPU), a graphics processing unit (GPU), or the like.

1030 The memoryis a main storage provided by a random access memory (RAM) or the like.

1040 1040 100 110 120 130 1030 1020 1040 150 The storage deviceis an auxiliary storage provided by a hard disk drive (HDD), a solid state drive (SSD), a memory card, a read only memory (ROM), or the like. The storage devicestores program modules providing the functions of the information processing apparatus(such as the image processing unit, the risk information generation unit, and the display control unit). By reading each program module into the memoryand executing the program module by the processor, each function related to the program module is provided. Further, the storage devicealso functions as the storage unit.

1050 10 The input-output interfaceis an interface for connecting the image processing apparatusto various types of input-output equipment.

1060 10 1060 10 20 1060 The network interfaceis an interface for connecting the image processing apparatusto a network. Examples of the network include a local area network (LAN) and a wide area network (WAN). The method for connecting the network interfaceto the network may be a wireless connection or a wired connection. The image processing apparatusmay communicate with the image capture apparatusthrough the network interface.

5 FIG. 10 110 10 10 110 20 110 20 110 is a flowchart illustrating a first example of processing performed by the image processing apparatus. First, the image processing unitin the image processing apparatusacquires an image to be processed (Step S). Then, the image processing unitprocesses the image and computes the aforementioned first distance for each person included in the image (Step S). In the computation, the image processing unitcomputes a first distance by using the height and the position of a person being a subject of computation of a distance in the image and the orientation of an image capture apparatusgenerating the image in the vertical direction. At this time, as details will be described later, the image processing unituses a value preset as the height of a person (hereinafter described as a reference height).

20 120 30 2 FIG. Next, by using the first distance generated in Step S, the risk information generation unitgenerates infection risk information. An example of the method for generating infection risk information is as described by using(Step S).

130 140 130 40 Then, the display control unitcauses the display unitto display the generated infection risk information. At this time, the display control unitmay cause the infection risk information to be displayed along with the image (may be the dynamic image) used to generate the infection risk information (Step S). Examples of an image displayed here will be described later.

6 FIG. 5 FIG. 20 110 110 is a diagram illustrating an example of the method for computing a first distance performed in Step Sin. The image processing unitdetermines a reference person. Then, the image processing unitperforms processing illustrated in this diagram on each person positioned around the reference person.

110 110 110 First, the image processing unitcomputes a height t of the reference person or a person positioned around the reference person in the image. For example, the height is represented by a pixel count. Next, the image processing unitcomputes a distance d from the reference person to a person positioned around the reference person in the image. Note that d is represented in the same unit as t (such as a pixel count). Next, the image processing unitcomputes d/t and, by multiplying the value by the aforementioned reference height, computes the distance between the reference person and the person positioned around the reference person.

When there is only one person around the reference person, the distance computed for the person is a first distance. Further, when there are a plurality of such persons, the aforementioned distance is computed for each of the plurality of persons, and the minimum value of the distances is a first distance.

20 20 150 110 20 150 Note that, as described above, the reference height is preset. The reference height may be changed according to a location where the image capture apparatusis installed (such as a country). For example, an average height of adults in a country where an image capture apparatusconsidered is installed is used as a reference height. As an example of specific processing, the storage unitstores information for determining a reference height for each piece of image capture apparatus-identification information. Then, the image processing unitacquires image capture apparatus-identification information of an image capture apparatusgenerating an image to be processed, reads a reference height related to the image capture apparatus-identification information from the storage unit, and uses the reference height.

110 Further, when an attribute (such as at least one of a gender and an age group) of a person being a subject of computation of the height t can be estimated by image processing, the image processing unitmay change the reference height, based on the attribute.

20 110 110 20 20 20 Note that, in most images, distortion peculiar to an image capture apparatusgenerating the image occurs. When computing a first distance, the image processing unitpreferably performs processing of correcting the distortion. The image processing unitperforms distortion correction processing based on the position of a person in an image. In general, distortion of an image is caused by, for example, an optical system (such as a lens) included in an image capture apparatusand the orientation (such as the angle relative to the horizontal plane) of the image capture apparatusin the vertical direction. Then, details of the distortion correction processing based on the position of the person in the image is set based on the optical system (such as a lens) included in the image capture apparatusand the orientation of the image capture apparatus in the vertical direction.

110 Note that, when an object the size of which is normalized to some extent is included in an image in the processing described by using this diagram, the image processing unitmay compute a first distance by using the size of the object in place of the height of a person.

7 FIG. 5 FIG. 7 FIG. 140 40 130 140 130 140 is a diagram illustrating a first example of an image displayed on the display unitin Step Sin. The display control unitcauses the display unitto display infection risk information along with the image (may be the dynamic image) used to generate the infection risk information. In the example illustrated in, the display control unitsuperimposes, on the image, a display for causing recognition of a combination of persons the first distance between whom has the reference value or less and then causes the display unitto display the display and the image.

130 140 110 130 As an example, the display control unitcauses the display unitto display a mark indicating a combination of persons recognized by the image processing unit. Then, the display control unitchanges the style of the mark, based on whether or not the first distance has the reference value or less. More specifically, in the example illustrated in this diagram, two persons constituting a combination of persons are enclosed by a circle or an ellipse. Then, the display color and/or the line style (such as a solid line, a dotted line, or a dot-and-dash line) of the circle or the ellipse is changed based on whether or not the first distance has the reference value or less.

7 FIG. 8 FIG. 7 FIG. 8 FIG. 1 2 4 Note that, when a displayed image is a dynamic image, a combination of persons being a subject of computation of a first distance changes as time elapses, as illustrated inand. For example, a person Pis the counterpart to a person Pin computation of a first distance at a timing in, whereas a person Pis the counterpart in computation of a first distance at a later timing in.

17 FIG. 18 FIG. 5 FIG. 17 FIG. 18 FIG. 17 FIG. 18 FIG. 140 40 130 130 1 2 3 3 4 5 6 andare diagrams illustrating a second example of an image displayed on the display unitin Step Sin. In these diagrams, for each person, the display control unitcauses a mark indicating a range of a recommended value (such as the aforementioned reference value) of a social distance around the person to be displayed. Then, when the mark related to a person overlaps the mark related to a nearby person, in other words, when the distance between a person and a nearby person has the recommended value of a social distance or less (for example, persons Pand Pinand), the marks related to the two persons are displayed in a style different from a mark related to another person (such as a person Pinand persons P, P, P, and Pin). Examples of the method for differentiation between styles include changing the display color and changing the line style (such as a solid line, a dotted line, or a dot-and-dash line) constituting the mark. For example, when changing the display color, the display control unitcauses the mark for a normal state to be displayed in blue and as for two marks overlapping each other, causes the two marks to be displayed in red.

17 FIG. 18 FIG. 17 FIG. 18 FIG. 130 130 140 In the example illustrated in, the display control unitsuperimposes the aforementioned marks on an image (may be a dynamic image) used to generate infection risk information. On the other hand, in the example illustrated in, placement of persons is indicated in a plan view and then the aforementioned marks are superimposed on the plan view. The display control unitmay cause the display illustrated inand the display illustrated into be displayed simultaneously on the display unit.

7 FIG. 8 FIG. 17 FIG. 18 FIG. 140 The displays illustrated in,,, andmay be displayed by using a real-time dynamic image or image. In this case, for example, the displays illustrated in the diagrams may be displayed on the display unitinstalled near a target region or may be used as a content of the Internet or broadcasting.

9 FIG. 5 FIG. 10 110 22 30 is a flowchart illustrating a second example of the processing performed by the image processing apparatus. The example illustrated in this diagram is similar to the example illustrated inexcept that the image processing unitalso computes a second distance when computing a first distance (Step S) and generates infection risk information by further using the second distance (Step S).

120 110 120 The second distance is a distance from a reference person to the second closest person to the reference person. A method for computing a second distance is similar to the method for computing a first distance except for selecting a distance to the second closest person instead of the closest person. Then, the risk information generation unitgenerates infection risk information in such a way that a risk increases (a safety factor decreases) as the second distance decreases. Note that the image processing unitmay further generate a distance from a reference person to the third closest person to the reference person (third distance). In this case, the risk information generation unitgenerates infection risk information by further using the third distance.

10 FIG. 5 FIG. 9 FIG. 10 120 is a flowchart illustrating a third example of the processing performed by the image processing apparatus. The example illustrated in this diagram is similar to the example illustrated inorexcept for further using information other than a distance between persons when the risk information generation unitgenerates infection risk information.

10 20 22 110 24 5 FIG. 9 FIG. Specifically, Step Sand Step S(or Step S) are similar to the example illustrated in(or). Then, by processing an image, the image processing unitgenerates additional information required for generating infection risk information. The generated information is at least one of a determination result of the orientation of the face of a person, a determination result of existence of a wearing article on the face and the type thereof, and a determination result of movement of the mouth of the person (Step S).

120 110 120 “The orientation of the face of a person” includes at least one of the orientation of the face of a reference person and the orientation of the face of the closest person to the reference person. Then, the risk information generation unitincreases a risk indicated by the infection risk information (decreases a safety factor) as the face of a person approaches toward such a direction as to face the counterpart. When using a second distance and a third distance, the image processing unitand the risk information generation unitmay further use the orientation of the face of a person serving as a counterpart when the second distance is computed and the orientation of the face of a person serving as a counterpart when the third distance is computed.

120 110 120 “Existence of a wearing article on the face” includes at least one item out of existence of a wearing article on a reference person and existence of a wearing article on the closest person to the reference person. Then, when a specific type of wearing article is detected, the risk information generation unitdecreases a risk indicated by the infection risk information (increases the safety factor) relative to other cases. The specific type of wearing article refers to an article covering at least one of (preferably both of) the mouth and the nose, such as a face mask or a scarf. When using a second distance and a third distance, the image processing unitand the risk information generation unitmay further perform similar processing on a person serving as a counterpart when the second distance is computed and a person serving as a counterpart when the third distance is computed.

120 110 120 “Movement of the mouth” means that at least the mouth is moving. When the mouth is moving, the person is highly likely to be speaking. Then, when the mouth of at least one of a reference person and the closest person to the reference person is moving, the risk information generation unitincreases a risk indicated by the infection risk information (decreases the safety factor) relative to other cases. When using a second distance and a third distance, the image processing unitand the risk information generation unitmay further use movement of the mouth of a person serving as a counterpart when the second distance is computed and movement of the mouth of a person serving as a counterpart when the third distance is computed.

11 FIG. 5 FIG. 9 FIG. 10 FIG. 10 10 is a flowchart illustrating a fourth example of the processing performed by the image processing apparatus. The image processing apparatusperforms processing illustrated in this diagram in addition to the processing illustrated in,, or.

20 110 110 120 In the example illustrated in this diagram, the image capture apparatusis a fixed camera. Therefore, each position in an image corresponds to a specific position in a target region. The image processing unitpreviously stores the correspondence relation. Then, the image processing unitidentifies a location where a proximity indicator being an indicator related to a proximity state between a plurality of persons satisfies a criterion (hereinafter described as a caution-requiring location). Then, the risk information generation unit(an example of an output unit) outputs information indicating the caution-requiring location.

110 10 20 22 110 150 5 FIG. 10 FIG. 9 FIG. More specifically, the image processing unitin the image processing apparatusidentifies a position in the target region where the first distance has the reference value or less by identifying a position in the image where the first distance has the reference value or less in Step Sinandor Step Sin. Then, the image processing unitcauses the storage unitto store information indicating the position in association with the processed image.

120 10 150 Then, the risk information generation unitin the image processing apparatustotals the number of times the first distance has a reference value or less in a target period (an example of the aforementioned proximity indicator) for each position in the target region by processing information stored in the storage unit. For example, the length of the target period may be one day, one week, or one month.

120 20 120 20 150 110 Specifically, first, the risk information generation unitacquires information for determining an image capture apparatusconsidered and information for determining the start and the end of a target period. For example, the acquisition is performed by input from a user. Next, the risk information generation unitreads an analysis result of images generated by the image capture apparatusconsidered in the target period from the storage unit. The read information includes information indicating the position where the first distance has the reference value or less. The information is generated for each image (Step S).

120 120 150 Further, the target region is previously divided into a plurality of parts. Then, the risk information generation unitcounts the number of times the first distance has the reference value or less for each of the plurality of parts (Step S). Note that the aforementioned “position where the first distance has the reference value or less” in the information stored in the storage unitmay be information indicating the part.

120 120 130 130 130 140 140 Then, the risk information generation unitoutputs information indicating a part where the count is a reference value or greater. The part indicated by the information is a part with a high infection risk, that is, a caution-requiring location. In the example illustrated in this diagram, the risk information generation unitoutputs information indicating the part. For example, the destination is the display control unit. In this case, the display control unitgenerates display information for displaying information that indicates the part (Step S) and causes the display unitto display the display information (Step S).

2 FIG. 110 110 As illustrated by using, the image processing unitcan compute the duration of a state in which the first distance has the reference value or less by processing a plurality of temporally continuous images. In this case, the image processing unitmay perform the aforementioned processing by counting the number of times the state in which the first distance has the reference value or less continues for a reference time or longer.

120 Further, the output performed by the risk information generation unitis used for identifying a location in a target region where persons tend to crowd together and improving such a location (for example, for improving a flow line of persons). As an example, when the target region is indoors, the output is used as reference data for changing placement and/or the number of objects (such as benches in a waiting room) placed in the indoors (such as a waiting room or a hallway). Note that examples of the flow line to be improved include a flow line from a waiting room to a consultation room in a hospital and a flow line from the entrance to a treatment room in a hospital.

120 While examples of the indoors include facilities such as a hospital, a public office, a station, and an airport, stores such as a large-scale store such as a shopping mall (including a case of being provided next to an airport or a station) may also be included. In the latter case, the output performed by the risk information generation unitidentifies a location where persons tend to crowd together in a building being a large-scale store. Then, the identification result is used as reference data when placement of tenants and a flow line are changed in order to prevent persons from crowding together in the location.

20 10 20 20 110 20 In the aforementioned example, a unit when setting a “caution-requiring location” is set by dividing one target region into a plurality of parts. On the other hand, a plurality of image capture apparatusesmay be connected to the image processing apparatus, and the plurality of image capture apparatusesmay capture images of locations different from each other in the same facility. In this case, a unit when setting a “caution-requiring location” may be an image capture region of one image capture apparatus(that is, one target region). To do so, the image processing unitmay count the number of times the first distance has the reference value or less or the number of times the state continues for the reference time or longer for each image capture apparatusinstead of for each of the aforementioned plurality of parts.

12 FIG. 11 FIG. 140 140 140 130 140 120 illustrates an example of a screen displayed on the display unitin Step Sin. In the example illustrated in this diagram, the display unitdisplays a plan view of a target region. Then, the display control unitcauses the display unitto display a part in the plan view where the count in Step Sis the reference value or greater in such a way that the part is distinguishable from another part.

120 120 130 Note that a plurality of values in stages may be set as reference values related to a count. In this case, the risk information generation unitdetermines which reference value is exceeded by the count in Step Sand outputs information indicating the value on which the determination is made. For example, the display control unitmay change the display style of the corresponding part, based on the output. For example, a part where only the lowest reference value is exceeded may be indicated in green, and a part where the highest reference value is exceeded may be indicated in red.

13 FIG. 5 FIG. 9 FIG. 10 FIG. 11 FIG. 10 10 10 is a flowchart illustrating a fifth example of the processing performed by the image processing apparatus. The image processing apparatusperforms processing illustrated in this diagram in addition to the processing illustrated in,, or. The image processing apparatusmay further perform the processing illustrated in.

120 10 In this diagram, the risk information generation unitin the image processing apparatusidentifies a timing when a risk of contracting an infectious disease increases (a timing when a safety factor decreases). For example, the timing is set for each day of the week, each time period, or each day of the week and each time period.

110 11 FIG. In the example illustrated in this diagram, processing described in Step Sis similar to the processing described by using.

120 122 120 11 FIG. Next, for each timing, the risk information generation unitcounts the number of times the first distance has the reference value or less (Step S). The risk information generation unitmay further perform per-timing counting for each of a plurality of parts in the target region as illustrated in.

120 120 130 130 130 140 140 Next, the risk information generation unitoutputs information indicating a timing when the count is the reference value or greater. The timing indicated by the information (such as a time period or a day of the week) is a timing with a high infection risk. As an example, the risk information generation unitoutputs the information indicating the timing to the display control unit. Then, the display control unitgenerates display information for displaying the information indicating the timing (Step S) and causes the display unitto display the display information (Step S).

140 130 130 Note that, when the target region is inside a store, the display unitmay be provided at the entrance of the store or in a show window. Thus, a person who intends to enter the store can recognize a timing when the store is less crowded. Further, the display control unitmay publish the display information generated in Step Son the Internet. Thus, a person planning to visit the store can recognize a timing when the store is considered less crowded.

140 130 140 140 7 FIG. 8 FIG. 17 FIG. 18 FIG. Further, when the target region is inside a store and the display unitis provided at the entrance of the store or in a show window, the display control unitmay cause the display unitto display current infection risk information or may cause the display unitto perform the displays illustrated in,,, andby using a real-time dynamic image or image.

14 FIG. 5 FIG. 9 FIG. 10 FIG. 11 FIG. 13 FIG. 10 10 10 is a flowchart illustrating a sixth example of the processing performed by the image processing apparatus. The image processing apparatusperforms processing illustrated in this diagram in addition to the processing illustrated in,, or. The image processing apparatusmay further perform at least one type of processing out of the processing illustrated inand the processing illustrated in.

120 150 20 In the example illustrated in this diagram, the risk information generation unitcauses the storage unitto store at least one of a history of past infection risk information and a result of statistical processing of the history for each of a plurality of image capture apparatuses, in other words, for each of a plurality of target regions. Note that the plurality of target regions are related to each other in a flow of persons. As an example, the plurality of target regions may adjoin each other or may exist along the same road or railroad (subway).

150 120 120 Then, when the storage unitstores only a history of past infection risk information, the risk information generation unitstatistically processes the history. Then, the risk information generation unitgenerates an estimation result of infection risk information at a predetermined future timing by using the result of statistical processing of the history of infection risk information, and the current infection risk information. For example, while the predetermined timing may be after one hour, after three hours, or after five hours, the timing is preferably within 24 hours. For example, the result of statistical processing of the history is a model generated by machine learning but is not limited thereto. Note that the model outputs an estimation result of infection risk information at a predetermined future timing when the current infection risk information is input.

20 120 210 120 First, by processing a current image generated by each of a plurality of image capture apparatusesinstalled in target regions different from each other, the risk information generation unitgenerates current infection risk information relating to each of the plurality of target regions (Step S). At this time, the risk information generation unitmay further process images generated between the present time and a predetermined time ago.

120 150 120 220 Next, the risk information generation unitacquires a result of statistical processing of the history of infection risk information relating to each of the plurality of target regions. The acquisition may be performed by readout from the storage unitor may be performed by on-the-fly statistical processing of the history of infection risk information. Next, the risk information generation unitgenerates an estimation result of infection risk information at the predetermined future timing by using the result of statistical processing of the history of infection risk information, and the current infection risk information (Step S).

130 120 230 140 240 Next, the display control unitgenerates display information for displaying the current infection risk information and the estimation result of infection risk information at the predetermined future timing, the pieces of information being generated by the risk information generation unit(Step S). By using the display information, the display unitdisplays the current infection risk information and the estimation result of infection risk information at the predetermined future timing (Step S). A person viewing the display can set a timing for taking an action (such as a timing for riding a train or a timing for going to a destination) to a timing with a lower infection risk.

120 120 Note that, when generating an estimation result of infection risk information at the predetermined future timing, the risk information generation unitmay determine an increasing or decreasing trend of the current infection risk information and use the determination result instead of performing statistical processing. For example, the risk information generation unitdetermines the increasing or decreasing trend by using changes in the number of times the first distance has the reference value or less from the past to the present.

15 FIG. 140 120 130 140 130 illustrates current infection risk information displayed on the display unit. As described above, the risk information generation unitgenerates infection risk information for each of a plurality of target regions. In the example illustrated in this diagram, the plurality of target regions represent a plurality of regions acquired by dividing one large area. Then, the display control unitcauses the display unitto display a target region where a risk indicated by infection risk information has a reference value or greater in a manner distinguishable from another target region. Note that the display control unitmay cause changes in infection risk information from the past to the present to be displayed in the processing.

16 FIG. 140 130 140 illustrates future infection risk information displayed on the display unit. In the example illustrated in this diagram, the display control unitcauses the display unitto display a target region where a risk indicated by future infection risk information has the reference value or greater in a manner distinguishable from another target region. When a plurality of target regions are related to each other in a flow of persons, generation of future infection risk information relating to a certain target region may be performed by using current infection risk information relating to the periphery of the target region. The reason is that a person in a certain target region may move to another target region after several hours.

15 FIG. 16 FIG. Note that the displays illustrated inandmay be published on the Internet or may be included in a television broadcast content.

110 10 20 120 20 As described above, according to the present example embodiment, for a person being at least part of a plurality of persons, the image processing unitin the image processing apparatuscomputes the distance to the closest person to the person (first distance) by acquiring and processing an image generated by the image capture apparatus, that is, an image including the plurality of persons. Then, the risk information generation unitgenerates infection risk information relating to a target region being an image capture target of the image capture apparatusby using the first distance. Therefore, the risk of contracting an infectious disease in the target region can be readily recognized.

120 140 Further, the risk information generation unitoutputs a location where a proximity indicator being an indicator related to a proximity state between a plurality of persons satisfies a criterion. For example, the output is displayed on the display unit. Thus, recognition of a location with a high possibility of contracting an infectious disease is facilitated.

While the example embodiments of the present invention have been described above with reference to the drawings, the example embodiments are exemplifications of the present invention, and various configurations other than those described above may be employed.

Further, while a plurality of processes (processing) are described in a sequential order in each of a plurality of flowcharts used in the aforementioned description, the execution order of processes executed in each example embodiment is not limited to the order of description. The order of the illustrated processes may be modified without affecting the contents in each example embodiment. Further, the aforementioned example embodiments may be combined without contradicting one another.

an image processing unit that, by processing an image including a plurality of persons, computes, for a person being at least part of the plurality of persons, a first distance being a distance to the closest person to the person; and a risk information generation unit that, by using the first distance, generates infection risk information being information about a risk of contracting an infectious disease or a safety factor of not contracting an infectious disease in a target region being a region included in the image. 1. An image processing apparatus including: the image processing unit further computes a second distance being a distance to a second closest person to the person, and the risk information generation unit generates the infection risk information by further using the second distance. 2. The image processing apparatus according to aforementioned 1, in which the image processing unit further determines at least one of an orientation of a face of the person and an orientation of a face of the closest person, and the risk information generation unit generates the infection risk information by further using a determination result of an orientation of the face. 3. The image processing apparatus according to aforementioned 1 or 2, in which the image processing unit further determines at least one of a wearing article on a face of the person and a wearing article on a face of the closest person, and the risk information generation unit generates the infection risk information by further using a determination result of the wearing article. 4. The image processing apparatus according to any one of aforementioned 1 to 3, in which the image processing unit further determines movement of a mouth of one of the person and the closest person, and the risk information generation unit generates the infection risk information by further using a determination result of movement of the mouth. 5. The image processing apparatus according to any one of aforementioned 1 to 4, in which the image processing unit computes the first distance by using a height and a position of the person in the image. 6. The image processing apparatus according to any one of aforementioned 1 to 5, in which further computes the first distance by using a reference height being a preset value and sets the reference height by using a location where the image is generated. the image processing unit 7. The image processing apparatus according to aforementioned 6, in which the risk information generation unit determines whether the first distance has a reference value or less and generates the infection risk information by using the determination result. 8. The image processing apparatus according to any one of aforementioned 1 to 7, in which a first display control unit that superimposes, on the image, a display for causing recognition of a combination of the person and the closest person the first distance between whom has a reference value or less and then causes a display unit to display the display and the image. 9. The image processing apparatus according to aforementioned 8, further including the image processing unit processes a plurality of the images in which the target region is captured at a plurality of timings, and counts, for each of a plurality of parts included in the target region, a number of times the first distance has a reference value or less in the part and outputs information indicating the part where the counting result satisfies a criterion. the risk information generation unit 10. The image processing apparatus according to aforementioned 8 or 9, in which the image processing unit processes a plurality of the images in which the target region is captured at a plurality of timings, and the risk information generation unit generates the infection risk information at each of the plurality of timings and determines a timing when the risk increases or a timing when the safety factor decreases by using the plurality of pieces of the infection risk information. 11. The image processing apparatus according to any one of aforementioned 1 to 10, in which the risk information generation unit generates an estimation result of the infection risk information at a predetermined future timing by using a result of statistical processing of a history of the past infection risk information, and the current infection risk information. 12. The image processing apparatus according to any one of aforementioned 1 to 11, in which the image processing unit generates the first distance for each of a plurality of target regions by processing an image generated for each of the plurality of the target regions, the risk information generation unit generates the infection risk information for each of the plurality of target regions, and the image processing apparatus further includes a second display control unit that causes a display unit to display a target region where a risk indicated by the infection risk information has a reference value or greater in a manner distinguishable from the another target region. 13. The image processing apparatus according to any one of aforementioned 1 to 12, in which performing image processing of, by processing an image including a plurality of persons, computing, for a person being at least part of the plurality of persons, a first distance being a distance to the closest person to the person; and performing risk information generation processing of, by using the first distance, generating infection risk information being information about a risk of contracting an infectious disease or a safety factor of not contracting an infectious disease in a target region being a region included in the image. 14. An image processing method including, by a computer: in the image processing, the computer further computes a second distance being a distance to a second closest person to the person, and, in the risk information generation processing, the computer generates the infection risk information by further using the second distance. 15. The image processing method according to aforementioned 14, in which, in the image processing, the computer further determines at least one of an orientation of a face of the person and an orientation of a face of the closest person, and, in the risk information generation processing, the computer generates the infection risk information by further using a determination result of an orientation of the face. 16. The image processing method according to aforementioned 14 or 15, in which, in the image processing, the computer further determines at least one of a wearing article on a face of the person and a wearing article on a face of the closest person, and, in the risk information generation processing, the computer generates the infection risk information by further using a determination result of the wearing article. 17. The image processing method according to any one of aforementioned 14 to 16, in which, in the image processing, the computer further determines movement of a mouth of one of the person and the closest person, and, in the risk information generation processing, the computer generates the infection risk information by further using a determination result of movement of the mouth. 18. The image processing method according to any one of aforementioned 14 to 17, in which, in the image processing, the computer computes the first distance by using a height and a position of the person in the image. 19. The image processing method according to any one of aforementioned 14 to 18, in which, further computes the first distance by using a reference height being a preset value and sets the reference height by using a location where the image is generated. in the image processing, the computer 20. The image processing method according to aforementioned 19, in which, in the risk information generation processing, the computer determines whether the first distance has a reference value or less and generates the infection risk information by using the determination result. 21. The image processing method according to any one of aforementioned 14 to in which, performing first display control of superimposing, on the image, a display for causing recognition of a combination of the person and the closest person the first distance between whom has a reference value or less and then causing a display unit to display the display and the image. 22. The image processing method according to aforementioned 21, further including, by the computer, in the image processing, the computer processes a plurality of the images counts, for each of a plurality of parts included in the target region, a number of times the first distance has a reference value or less in the part and outputs information indicating the part where the counting result satisfies a criterion. in which the target region is captured at a plurality of timings, and, in the risk information generation processing, the computer 23. The image processing method according to aforementioned 21 or 22, in which, in the image processing, the computer processes a plurality of the images in which the target region is captured at a plurality of timings, and, in the risk information generation processing, the computer generates the infection risk information at each of the plurality of timings and determines a timing when the risk increases or a timing when the safety factor decreases by using the plurality of pieces of the infection risk information. 24. The image processing method according to any one of aforementioned 14 to 23, in which, in the risk information generation processing, the computer generates an estimation result of the infection risk information at a predetermined future timing by using a result of statistical processing of a history of the past infection risk information, and the current infection risk information. 25. The image processing method according to any one of aforementioned 14 to 24, in which, in the image processing, the computer generates the first distance for each of a plurality of target regions by processing an image generated for each of the plurality of the target regions, in the risk information generation processing, the computer generates the infection risk information for each of the plurality of target regions, and the image processing method further includes, by the computer, performing second display control of causing a display unit to display a target region where a risk indicated by the infection risk information has a reference value or greater in a manner distinguishable from the another target region. 26. The image processing method according to any one of aforementioned 14 to 25, in which, an image function of, by processing an image including a plurality of persons, computing, for a person being at least part of the plurality of persons, a first distance being a distance to the closest person to the person; and a risk information generation function of, by using the first distance, generating infection risk information being information about a risk of contracting an infectious disease or a safety factor of not contracting an infectious disease in a target region being a region included in the image. 27. A program causing a computer to perform: the image processing function further computes a second distance being a distance to a second closest person to the person, and the risk information generation function generates the infection risk information by further using the second distance. 28. The program according to aforementioned 27, in which the image processing function further determines at least one of an orientation of a face of the person and an orientation of a face of the closest person, and the risk information generation function generates the infection risk information by further using a determination result of an orientation of the face. 29. The program according to aforementioned 27 or 28, in which the image processing function further determines at least one of a wearing article on a face of the person and a wearing article on a face of the closest person, and the risk information generation function generates the infection risk information by further using a determination result of the wearing article. 30. The program according to any one of aforementioned 27 to 29, in which the image processing function further determines movement of a mouth of one of the person and the closest person, and the risk information generation function generates the infection risk information by further using a determination result of movement of the mouth. 31. The program according to any one of aforementioned 27 to 30, in which the image processing function computes the first distance by using a height and a position of the person in the image. 32. The program according to any one of aforementioned 27 to 31, in which further computes the first distance by using a reference height being a preset value and sets the reference height by using a location where the image is generated. the image processing function 33. The program according to aforementioned 32, in which the risk information generation function determines whether the first distance has a reference value or less and generates the infection risk information by using the determination result. 34. The program according to any one of aforementioned 27 to 33, in which a first display control function of superimposing, on the image, a display for causing recognition of a combination of the person and the closest person the first distance between whom has a reference value or less and then causing a display unit to display the display and the image. 35. The program according to aforementioned 34, further causing the computer to perform the image processing function processes a plurality of the images in which the target region is captured at a plurality of timings, and counts, for each of a plurality of parts included in the target region, a number of times the first distance has a reference value or less in the part and outputs information indicating the part where the counting result satisfies a criterion. the risk information generation function 36. The program according to aforementioned 34 or 35, in which the image processing function processes a plurality of the images in which the target region is captured at a plurality of timings, and the risk information generation function generates the infection risk information at each of the plurality of timings and determines a timing when the risk increases or a timing when the safety factor decreases by using the plurality of pieces of the infection risk information. 37. The program according to any one of aforementioned 27 to 36, in which the risk information generation function generates an estimation result of the infection risk information at a predetermined future timing by using a result of statistical processing of a history of the past infection risk information, and the current infection risk information. 38. The program according to any one of aforementioned 27 to 37, in which the image processing function generates the first distance for each of a plurality of target regions by processing an image generated for each of the plurality of the target regions, the risk information generation function generates the infection risk information for each of the plurality of target regions, and the program further causes the computer to perform a second display control function of causing a display unit to display a target region where a risk indicated by the infection risk information has a reference value or greater in a manner distinguishable from the another target region. 39. The program according to any one of aforementioned 27 to 38, in which The whole or part of the example embodiments disclosed above may also be described as, but not limited to, the following supplementary notes.

This application is based upon and claims the benefit of priority from Japanese Patent Application No. 2020-098401, filed on Jun. 5, 2020, the disclosure of which is incorporated herein in its entirety by reference.

10 Image processing apparatus 20 Image capture apparatus 110 Image processing unit 120 Risk information generation unit 130 Display control unit 140 Display unit 150 Storage unit